feat: (Series|DataFrame).plot

bigframes/operations/plotting.py

@@ -23,31 +23,45 @@
 class PlotAccessor(vendordt.PlotAccessor):
     __doc__ = vendordt.PlotAccessor.__doc__
 
+    _common_kinds = ("line", "area", "hist")
+    _dataframe_kinds = ("scatter",)
+    _all_kinds = _common_kinds + _dataframe_kinds
+
+    def __call__(self, **kwargs):
+        import bigframes.series as series
+
+        if kwargs.pop("backend", None) is not None:
+            raise NotImplementedError(
+                f"Only support matplotlib backend for now. {constants.FEEDBACK_LINK}"
+            )
+
+        kind = kwargs.pop("kind", "line")
+        if kind not in self._all_kinds:
+            raise NotImplementedError(
+                f"{kind} is not a valid plot kind supported for now. {constants.FEEDBACK_LINK}"
+            )
+
+        data = self._parent.copy()
+        if kind in self._dataframe_kinds and isinstance(data, series.Series):
+            raise ValueError(f"plot kind {kind} can only be used for data frames")
+
+        return bfplt.plot(data, kind=kind, **kwargs)
+
     def __init__(self, data) -> None:
         self._parent = data
 
     def hist(
         self, by: typing.Optional[typing.Sequence[str]] = None, bins: int = 10, **kwargs
     ):
-        if kwargs.pop("backend", None) is not None:
-            raise NotImplementedError(
-                f"Only support matplotlib backend for now. {constants.FEEDBACK_LINK}"
-            )
-        return bfplt.plot(self._parent.copy(), kind="hist", by=by, bins=bins, **kwargs)
+        return self(kind="hist", by=by, bins=bins, **kwargs)
 
     def line(
         self,
         x: typing.Optional[typing.Hashable] = None,
         y: typing.Optional[typing.Hashable] = None,
         **kwargs,
     ):
-        return bfplt.plot(
-            self._parent.copy(),
-            kind="line",
-            x=x,
-            y=y,
-            **kwargs,
-        )
+        return self(kind="line", x=x, y=y, **kwargs)
 
     def area(
         self,
@@ -56,14 +70,7 @@ def area(
         stacked: bool = True,
         **kwargs,
     ):
-        return bfplt.plot(
-            self._parent.copy(),
-            kind="area",
-            x=x,
-            y=y,
-            stacked=stacked,
-            **kwargs,
-        )
+        return self(kind="area", x=x, y=y, stacked=stacked, **kwargs)
 
     def scatter(
         self,
@@ -73,12 +80,4 @@ def scatter(
         c: typing.Union[typing.Hashable, typing.Sequence[typing.Hashable]] = None,
         **kwargs,
     ):
-        return bfplt.plot(
-            self._parent.copy(),
-            kind="scatter",
-            x=x,
-            y=y,
-            s=s,
-            c=c,
-            **kwargs,
-        )
+        return self(kind="scatter", x=x, y=y, s=s, c=c, **kwargs)

tests/system/small/operations/test_plotting.py

@@ -233,3 +233,31 @@ def test_sampling_plot_args_random_state():
     msg = "numpy array are different"
     with pytest.raises(AssertionError, match=msg):
         tm.assert_almost_equal(ax_0.lines[0].get_data()[1], ax_2.lines[0].get_data()[1])
+
+
+@pytest.mark.parametrize(
+    ("kind", "col_names", "kwargs"),
+    [
+        pytest.param("hist", ["int64_col", "int64_too"], {}),
+        pytest.param("line", ["int64_col", "int64_too"], {}),
+        pytest.param("area", ["int64_col", "int64_too"], {"stacked": False}),
+        pytest.param(
+            "scatter", ["int64_col", "int64_too"], {"x": "int64_col", "y": "int64_too"}
+        ),
+        pytest.param(
+            "scatter",
+            ["int64_col"],
+            {},
+            marks=pytest.mark.xfail(raises=ValueError),
+        ),
+        pytest.param(
+            "uknown",
+            ["int64_col", "int64_too"],
+            {},
+            marks=pytest.mark.xfail(raises=NotImplementedError),
+        ),
+    ],
+)
+def test_plot_call(scalars_dfs, kind, col_names, kwargs):
+    scalars_df, _ = scalars_dfs
+    scalars_df[col_names].plot(kind=kind, **kwargs)

third_party/bigframes_vendored/pandas/plotting/_core.py

@@ -4,7 +4,43 @@
 
 
 class PlotAccessor:
-    """Make plots of Series or DataFrame with the `matplotlib` backend."""
+    """
+    Make plots of Series or DataFrame with the `matplotlib` backend.
+
+    **Examples:**
+    For Series:
+
+        >>> import bigframes.pandas as bpd
+        >>> ser = bpd.Series([1, 2, 3, 3])
+        >>> plot = ser.plot(kind='hist', title="My plot")
+
+    For DataFrame:
+
+        >>> df = bpd.DataFrame({'length': [1.5, 0.5, 1.2, 0.9, 3],
+        ...                   'width': [0.7, 0.2, 0.15, 0.2, 1.1]},
+        ...                   index=['pig', 'rabbit', 'duck', 'chicken', 'horse'])
+        >>> plot = df.plot(title="DataFrame Plot")
+
+    Args:
+        data (Series or DataFrame):
+            The object for which the method is called.
+        kind (str):
+            The kind of plot to produce:
+
+            - 'line' : line plot (default)
+            - 'hist' : histogram
+            - 'area' : area plot
+            - 'scatter' : scatter plot (DataFrame only)
+
+        **kwargs:
+            Options to pass to `pandas.DataFrame.plot` method. See pandas
+            documentation online for more on these arguments.
+
+    Returns:
+            matplotlib.axes.Axes or np.ndarray of them:
+                An ndarray is returned with one :class:`matplotlib.axes.Axes`
+                per column when ``subplots=True``.
+    """
 
     def hist(
         self, by: typing.Optional[typing.Sequence[str]] = None, bins: int = 10, **kwargs